lapply(pre2016list, function1)
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This is all well and good. But I found it difficult to remember which zone went where. So I’ve plotted a reference image to go beside the charts. #Pre-2016 Reference Images
arransubsect <- filter(pcs,substr(label,1,4)=="KA27")
lapply(pre2016list, function2)
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But thinking about it, I could plot all the years together like this. #Pre-2016 Individual Zones shown on whole island
lapply(pre2016list, function3)
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Post-2016
lapply(post2016list, function1)
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lapply(post2016list, function2)
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lapply(post2016list, function3)
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Plot the percentiles as bar charts.
arransimd %>%
ggplot(aes(x=year, y=Percentile)) +
geom_bar(stat="identity") +
facet_wrap('DataZone') +
labs(title = "Arran SIMD Datazones", x = "Year", y = "Percentile") +
theme(plot.title = element_text(hjust = 0.5))

Splitting the bar charts up.
Ideally now I’d like to annotate the above data to highlight the 2016 plots, and show where the change in DZ occurs. (I.e draw a polygon around S01011171-S01011177). I don’t know how to do that yet, so what I’ll do now is seperate it into 2 plots.
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